基于灰熵关联分析的流水车间多目标调度优化及算法实现  

Flow shop multi-objective scheduling optimization research based on grey entropy relation analysis and the algorithm realization

作　　者：朱光宇[1] 陈旭斌[1] 刘艳立[1,2] 

机构地区：[1]福州大学机械工程及自动化学院,福州350108 [2]山推工程机械股份有限公司,山东济宁272073

出　　处：《控制与决策》2014年第1期135-140,共6页Control and Decision

基　　金：福建省高等学校新世纪优秀人才支持计划项目(XSJRC2007-08);福建省自然科学基金项目(2009J01246);福建省教育厅项目(JK2013006)

摘　　要：求解流水车间多目标调度优化问题及算法适应度值分配问题,结合灰色关联度分析方法及信息熵理论提出灰熵关联度适应值分配策略,利用灰关联系数结合熵值权重计算适应度值,以灰熵关联度值引导启发式算法进化.将该方法应用到差分算法及遗传算法中解决三目标流水车间调度问题.实验表明:灰熵关联度适应值分配策略能够解决该问题,可以得到分布均匀的Pareto前端;同时,基于此策略的差分算法得到的解好于遗传算法的解.In order to solve the flow shop multi-objective scheduling optimization problem and the algorithm fitness value assignment problem, the distribution strategy of the grey entropy relational adaptive value is proposed combined with grey correlation analysis method and the theory of the information entropy, and the fitness value is calculated combined with the grey correlation and entropy weight coefficient. The grey entropy correlation grade is used to guide the evolution of the heuristic algorithm. This method is introduced to the difference algorithm and the genetic algorithm to solve three objective flow shop scheduling problem. The experimental results show that grey entropy relational adaptive value allocation strategies can solve this problem effectively, and can get uniform distribution of the Pareto front. Meanwhile, the difference algorithm based on this strategy can abtain better solutions than the genetic algorithm.

关 键 词：流水车间调度 多目标优化 灰熵关联分析 灰熵关联度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]